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--- public:t-720-atai:atai-19:readings [2019/09/02 09:18] – [Deifinitions of Artificial Intelligence] thorisson
+++ public:t-720-atai:atai-19:readings [2024/04/29 13:33] (current) – external edit 127.0.0.1
@@ Line 19: / Line 19: @@
 **As you read papers from each of the following categories I want you ask yourself a few questions:**
-  * For each category X, ask:
+  * For each paper in each category X, ask yourself:
     * What is X?
     * How does the human mind do X?
     * Do current computers do X?
     * ...and ...
-    * Do we need X to create a machine that rivals the ability of humans to do X?
+    * Do we need (to replicate or capture) what the human mind does to achieve X to create a machine that rivals the ability of humans to do X?
 If you can answer them satisfactorily when you're done reading you're good! Even if you can't you'll be fine if you: Write down the discrepacies and //bring them to class in the form of questions//. There is no such thing as a 'stupid question' when you're learning something new.
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+===== Intelligence =====
-==== Intelligence ====
+====Prerequisites====
-===Prerequisites===
   * [[http://en.wikipedia.org/wiki/General_intelligence_factor| The g factor]] on Wikipedia.
   * [[http://en.wikipedia.org/wiki/Theory_of_multiple_intelligences| Multiple theory of intelligence]] on Wikipedia.
-===Key Papers===
+====Key Papers====
   * [[http://www.vetta.org/documents/A-Collection-of-Definitions-of-Intelligence.pdf|A Collection of Definitions of Intelligence]] by Legg & Hutter.
@@ Line 46: / Line 47: @@
   * [[http://consc.net/papers/emergence.pdf|Strong and Weak Emergence]] by D. Chalmers
   * Animals //(you are encouraged to find other material on these topics - please let instructor know if you find some good stuff)//.
-    * [[https://www.youtube.com/watch?v=dKvVaRlz0Y4|Alex the Parrot]] on YouTube (video repeats halfway).  [[https://en.wikipedia.org/wiki/Alex_(parrot)|Alex on Wikipedia]] |
+    * [[https://www.youtube.com/watch?v=dKvVaRlz0Y4|Alex the Parrot]] on YouTube (video repeats halfway).  [[https://en.wikipedia.org/wiki/Alex_(parrot)|Alex on Wikipedia]]
-    * [[https://www.youtube.com/watch?v=SNuZ4OE6vCk|Koko the Gorilla]] on YouTube.  [[https://en.wikipedia.org/wiki/Koko_(gorilla)|Koko on Wikipedia]] |
+    * [[https://www.youtube.com/watch?v=SNuZ4OE6vCk|Koko the Gorilla]] on YouTube.  [[https://en.wikipedia.org/wiki/Koko_(gorilla)|Koko on Wikipedia]]
+    * [[https://www.youtube.com/watch?v=exsrX6qsKkA|Bumblebees learn by observation]] on YouTube. [[https://www.researchgate.net/publication/272748457_Information_transfer_beyond_the_waggle_dance_Observational_learning_in_bees_and_flies|Paper on Bumblebees learning by observation]] by Loukola et al.
     * [[https://apple.news/AQEvvY_wbRdqE1J-3MU_6WQ|Why Aren't Elephants Smarter Than Humans Since Their Brains Are Bigger?]] by Fabian van den Berg
     * [[https://www.youtube.com/watch?v=BG-0Bpe0J34|Parrots vs. Children]] BBC Earth on YouTube
@@ Line 74: / Line 76: @@
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-==== Constructionist Systems & Methodologies ====
+===== Constructionist Systems & Methodologies =====
-===Prerequisites===
+====Prerequisites====
   * [[http://www.gatsby.ucl.ac.uk/~dayan/papers/dw01.pdf|Reinforcement Learning in the Encyclopedia of Cognitive Science]] by Peter Dayan and Christopher Watkins.
   * [[http://www.ualberta.ca/~szepesva/RLBook.html|Algorithms for Reinforcement Learning]] by Csaba Szepesvári (2010) is a much more recent, shorter book that discusses the strengths and weaknesses of various RL algorithms. See also: [[http://incompleteideas.net/sutton/RL-FAQ.html|Rich Sutton's FAQ]].
-  * [[https://en.wikipedia.org/wiki/Deep_learning|Deep learning on Wikipedia]] (Chapters: Intro, Overview, and Neural Networks).
+  * [[https://en.wikipedia.org/wiki/Deep_learning|Deep learning on Wikipedia]] (Sections: Intro, Overview, and Neural Networks).
   * [[https://www.youtube.com/watch?v=2pWv7GOvuf0|Introduction to RL]] video by D. Silvers.
+  * [[https://en.wikibooks.org/wiki/Control_Systems/System_Metrics|Control systems: 'Type' and 'order']] on Wikibooks
-=== Introductory Material - Constructionist AI [ 2,3 ] ===
+==== Introductory Material - Constructionist AI [ 2,3 ] ====
   * {{:public:intro_to_software_arch.pdf| Introduction to Software Architecture}} by Garlan & Shaw.
@@ Line 92: / Line 95: @@
   * [[http://people.csail.mit.edu/brooks/papers/how-to-build.pdf|How to Build Complete Creatures Rather than Isolated Cognitive Simulators]] by Rodney Brooks
   * [[http://alumni.media.mit.edu/%7Ekris/ftp/IJAAI.pdf|A Mind Model for Multimodal Communicative Creatures and Humanoids]] by Thórisson, K. R.
+  * [[http://www.artificialhumancompanions.com/robot-mind-robot-body-whatever-happened-subsumption-architecture/|Whatever happened to the subsumption architecture?]] by Simon Birrell
+==== Limitations of Constructionist AI [ 2,4 ] ====
-=== Limitations of Constructionist AI [ 2,4 ] ===
   * {{:public:archmismatch-icse17.pdf| Architectural Mismatch or Why it’s hard to build systems out of existing parts}} by Garlan, D., R. Allen and J. Ockerbloom. Also available [[http://www.cs.cmu.edu/afs/cs/project/able/ftp/archmismatch-icse17/archmismatch-icse17.pdf|here]].
@@ Line 104: / Line 108: @@
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-==== The Holy Grail of AI: Generality ====
+===== The Holy Grail of AI: Generality =====
-=== Overview of Artificial General Intelligence [ 4,5 ] ===
+==== Overview of Artificial General Intelligence [ 4,5 ] ====
   * [[http://cadia.ru.is/wiki/public:t720-atai-2012:what_is_agi|What is AGI?]] by K. R. Thórisson.
@@ Line 115: / Line 119: @@
   * [[http://act-r.psy.cmu.edu/wordpress/wp-content/uploads/2012/12/526FSQUERY.pdf|(ACT-R) An Integrated Theory of the Mind]] by Anderson, J. R.; Bothell, D.; Byrne, M.D.; Douglass, S.; Lebiere, C. & Qin, Y.
-=== Requirements for AGI [ 3,5 ] ===
+==== Requirements for AGI [ 3,5 ] ====
 Related to: //Methodology, Cognitive Architectures//
@@ Line 124: / Line 128: @@
   * [[https://iccm-conference.neocities.org/2007/files/wray__lebiere__weinstein__jha__springer__belding__best____van_parunak.pdf| Towards a Complete, Multi-level Cognitive Architecture]] by R. Wray et al.
-=== Thought, Cognition, Cognitive Process/es ===
+==== Thought, Cognition, Cognitive Process/es ====
 Related to: //Cognitive Architecture, Intelligence, Understanding, AI //
@@ Line 134: / Line 138: @@
-=== Understanding [ 3,4 ]===
+==== Understanding [ 3,4 ]====
 Related to: //Thought, Reasoning//
   * [[http://alumni.media.mit.edu/~kris/ftp/AGI16_understanding.pdf|About Understanding]] by K. R. Thorisson et al.
   * [[http://alumni.media.mit.edu/~kris/ftp/IJCAI17-EGPAI-EvaluatingUnderstanding.pdf|Evaluating Understanding]] by K.R. Thórisson & J. Bieger
-  * [[http://alumni.media.mit.edu/~kris/ftp/AGI17_Understanding&CommonSense.pdf|Understanding & Common Sense]] by K. R. Thórisson & J. Bieger
+  * [[http://alumni.media.mit.edu/~kris/ftp/AGI17_Understanding&CommonSense.pdf|Understanding & Common Sense]] by K. R. Thórisson & D. Kremelberg
   * [[http://alumni.media.mit.edu/~kris/ftp/AGI17-UUW-DoMachinesUnderstand.pdf|Do Machines Understand? A Short Review of Understanding & Common Sense in Artificial Intelligence]]  by K.R. Thórisson & D. Kremelberg
-=== Situatedness, Embodiment [ 1,2 ] ===
+==== Situatedness, Embodiment [ 1,2 ] ====
 Related to: //Symbols, Meaning, Autonomy, Bootstrapping //
@@ Line 151: / Line 155: @@
-=== Autonomy [ 3,4 ]===
+==== Autonomy [ 3,4 ]====
 Related to: //Bootstrapping / Self-Programming//
@@ Line 161: / Line 165: @@
-=== Resource Control: Attention / Self-Control / Integrated Cognitive Control [ 4,6 ] ===
+==== Resource Control: Attention / Self-Control / Integrated Cognitive Control [ 4,6 ] ====
 Related to: //Cognitive Architecture, Learning//
@@ Line 176: / Line 180: @@
-=== Self-Programming [ 4,5 ] ===
+==== Self-Programming [ 4,5 ] ====
 Related to: //Reasoning, Learning, Bootstrapping//
@@ Line 185: / Line 189: @@
-=== Reasoning  [ 4,6 ]===
+==== Reasoning  [ 4,6 ]====
 Related to: //Thought, Cognitive Architecture, Intelligence//
@@ Line 196: / Line 200: @@
-=== (AGI) Bootstrapping / Seed A(G)I / Seed Programming [ 2,4 ] ===
+==== (AGI) Bootstrapping / Seed A(G)I / Seed Programming [ 2,4 ] ====
 Related to: //Cognitive Architecture, Intelligence//
@@ Line 205: / Line 209: @@
-=== Learning ===
+==== Learning ====
 Related to: //Resource control, Attention, Reasoning//
   * [[http://alumni.media.mit.edu/~kris/ftp/AGI16_growing_recursive_self-improvers.pdf|Growing Recursive Self-Improvers]] by B. Steunebrink et al.
@@ Line 214: / Line 218: @@
-=== Artificial Pedagogy [ 2,4 ] ===
+==== Artificial Pedagogy [ 2,4 ] ====
 Related to: //Learning, Bootstrapping//
@@ Line 227: / Line 231: @@
-=== AGI Methodology [ 5,6 ] ===
+==== AGI Methodology [ 5,6 ] ====
 Related to: //Cognitive Architecture, Implemented AGI Systems //
@@ Line 241: / Line 245: @@
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 \\
-====Implemented AGI-Aspiring Systems====
+=====Implemented AGI-Aspiring Systems=====
-=== NARS [ 4,5 ] ===
+==== NARS [ 4,5 ] ====
   * [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.134.4298&rep=rep1&type=pdf|From NARS to a thinking machine]] by P. Wang
@@ Line 252: / Line 256: @@
-=== AERA [ 5,5 ]===
+==== AERA [ 5,5 ]====
   * [[http://alumni.media.mit.edu/~kris/ftp/PeeweeGranularity-Thorisson-Nivel-09.pdf|Achieving Artificial General Intelligence Through Peewee Granularity]] by Thórisson, K. R. & Nivel, E.
@@ Line 262: / Line 266: @@
-=== Sigma [ 0,1 ] ===
+==== Sigma [ 0,1 ] ====
   * [[http://cs.usc.edu/~rosenblo/Pubs/Sigma%20AISBQ%20D.pdf|The Sigma Cognitive Architecture and System]] by P. S. Rosenbloom.
-=== Open Cog [ 0,2 ] ===
+==== Open Cog [ 0,2 ] ====
   * [[http://goertzel.org/dynapsyc/2009/OpenCogPrime.pdf|OPENCOG PRIME: A COGNITIVE SYNERGY BASED ARCHITECTURE FOR ARTIFICIAL GENERAL INTELLIGENCE]] by Ben Goerzel.
   * [[http://wiki.opencog.org/w/Getting_Started|Getting Started with Open Cog]] by Ben Goerzel.
-=== Other Such Systems [ 0,3 ] ===
+==== Other Such Systems [ 0,3 ] ====
   * Franklin, S. (2007). **(LIDA) A Foundational Architecture for Artificial General Intelligence**. Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms. IOS Press, Amsterdam, The Netherlands, The Netherlands, pp. 36-54. [[http://goertzel.org/agiri06/%5B4%5D%20StanFranklin.pdf | PDF]]
@@ Line 282: / Line 286: @@
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-==== Evaluation: Worlds, Tasks, Environments [ 3,6 ] ====
+===== Evaluation: Worlds, Tasks, Environments [ 3,6 ] =====
   * [[http://alumni.media.mit.edu/~kris/ftp/EGPAI_2016_paper_9.pdf|Evaluation of General-Purpose Artificial Intelligence: Why, What & How]] by J. Bieger et al.
@@ Line 355: / Line 359: @@
   * [[http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html|Advanced Topics: RL]] by David Silver is a more in-depth, modern RL course from one of the people who worked on Google DeepMind's Atari playing system that received a lot of (media) attention.
   * [[http://videolectures.net/nips09_littman_mbrl/|Model-Based Reinforcement Learning]] is a tutorial given by Michael Littman at NIPS'09 about model-based RL, which is a lot less common than model-free RL, but not less interesting.
+  * [[http://link.springer.com/chapter/10.1007/978-3-642-39521-5_13#page-1|Resource-Bounded Machines are Motivated to be Effective, Efficient & Curious]] by B. Steunebrink
 === Deep Learning [ 0,1 ]===